mahout hadoop

The source file for mahout seq2sparse is sparsevectorsfromsequencefiles. java. First use documentprocessor. the tokenizedocuments method, and the documentprocessor class is described as follows in the mahout API documentation: "This class converts a set of input parameters ENTs in the sequence file format of stringtuples. the sequencefile input shoshould haveText keyContaining the unique document identifi

Kmeans data for http://archive.ics.uci.edu/ml/databases/synthetic_control/synthetic_control.data1. Start hadoop $ Hadoop_home/bin/start-all.sh Copy Data to HDFS $ Hadoop_home/bin/hadoop FS-mkdir testdata $ hadoop_home/bin/hadoop FS-put (HDFS input directory name shocould be testdata) 2. Run mahout. $ Mahout_ho

The installation of Mahout under Ubuntu10.04 is basically mastered, the detailed installation steps are given below, with software requirements: 1. jdk-6u27-linux-i586.bin2.apache-maven-2.2.1-bin.t I have mastered the installation of Mahout in Ubuntu 10.04. The installation steps are as follows, as shown in the figure below. 1 software requirements: 1. jdk-6u27-linux-i586.bin 2. apache-maven-2.2.1-bin.tar.g

hadoop1.0.4,mahout0.7. A recent update on the platform for the previously written web call Mahout algorithm added some basic operations for Hadoop and added Mahout two algorithms, which are expected to be posted to the CSDN resource page in two days. Students who need to download the reference. Today, the problem is to call the

):1. Read the model. The parameter model path, the label's encoding file (Labelindex.bin). The number of tags (labelnumber), according to the relevant path, the initialization of model-related variables;2. For each record. For example 0.2,0.3,0.4. According to the SV (input path vector delimiter), this record is quantized to obtain vector (0=0.2,1=0.3,2=0.4);3. Using the model to calculate the score of each label, the resulting is also a vector that records the scores of each label vector result

In the mahout_in_action book, there is a simple example of kmeans.Source codeDoes not indicate which packages to import to run correctly This book begins with a reference to allCodeAll of them are based on mahout0.4, but I found that the kmeans example is based on mahout0.3. There are several functions not available in version 0.4. I don't know if it is because I directly used the compiled package, but I did not check the source code of mahout0.4. Below I will mark which functions are not fo

Apache mahout 0.2 is released. mahout is a sub-project of Apache Lucene. It implements various machine learning and Data Mining Based on hadoop.AlgorithmLibrary and mahout 0.2 highlights: Performance Improvement and API update of the collaborative filtering engine Implementation of K-nearest neighbor and SVD recommendation algorithm Random forest (random fores

Mahout's Chinese meaning: Elephant husbandMahout origins2008 became Lucene's son, Lucene as a search engine,There is a lot of textual data analysis and mining requirements (such as text repetition, automatic text classification, etc.),This led to some of the developers in the Lucene project turning to the machine learning domain to research algorithms that eventually formed the initial mahout of these machine learning algorithms.Absorbing open source

Original address: http://blog.fens.me/hadoop-family-roadmap/Sep 6,Tags:hadoophadoop familyroadmapcomments:CommentsHadoop Family Learning RoadmapThe Hadoop family of articles, mainly about the Hadoop family of products, commonly used projects include Hadoop, Hive, Pig, HBase, Sqoop,

First of all, the source code analysis of the mahout association rules in the previous article is incorrect in many parts of part2. Now I will re-write the following: run the following command on the command line to obtain the usage of the association rule FPGrowthDriver for mahout: [java] bin/hadoop jar $ mahout_home/core/target/

discriminant analysis Evolutionary algorithms Parallelization of the Watchmaker framework Recommended/Collaborative filtering Non-distributed recommenders Taste (USERCF, ITEMCF, Slopeone) Distributed recommenders Itemcf Calculation of vector similarity Rowsimilarityjob Calculate the similarity between columns Vectordistancejob Calculate distance between vectors Non-map-reduce algorithm H

The main introduction to the Hadoop family of products, commonly used projects include Hadoop, Hive, Pig, HBase, Sqoop, Mahout, Zookeeper, Avro, Ambari, Chukwa, new additions include, YARN, Hcatalog, O Ozie, Cassandra, Hama, Whirr, Flume, Bigtop, Crunch, hue, etc.Since 2011, China has entered the era of big data surging, and the family software, represented by

It is not absolutely necessary to generate recommendation results by estimating preference values. Providing a recommended list from superior to inferior is sufficient for many scenarios without having to include the estimated preference value. Precision: Ratio of the relevant results in the top results Full query rate: Percentage of all relevant results included in the top results Test the previous example: Package mahout; import Java. io. file; impo

1. Build a Java Project project name on Elcipse: mymahout2. Create the Libs folder and find the Java package under the Mahout 0.9 lib folderWhere log4j.properties can be found under the Hadoop folder.Put them under the Libs folder.3. Copy the folder Libs to the Mymahout project4. Click the Libs folder, right, select Build Path, and bring the file under the Libs folder.5. Create the class